An Overall Ship Propulsion Model for Fuel Efficiency Study

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Peer-review under responsibility of Applied Energy Innovation Institute doi: 10.1016/j.egypro.2015.07.139

Energy Procedia 75 ( 2015 ) 813 – 818

ScienceDirect

The 7

th

_{International Conference on Applied Energy – ICAE2015}

An Overall Ship Propulsion Model for Fuel Efficiency Study

Feiyang Zhao

a

_{*, Wenming Yang}

a,b

_{, Woei Wan Tan}

a,c

_{, Siaw Kiang Chou}

b

_,

Wenbin Yu

b

a_{Centre for Maritime Studies, National University of Singapore, Singapore 117576, Singapore} b_{Department of Mechanical Engineering, National University of Singapore, Singapore 117576, Singapore} c_{Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore}

Abstract

An overall ship propulsion plant involving marine engine, propeller and ship dynamic model was presented in this work. The cycle mean value model was utilized to describe the operation process in engine dynamic, intake/exhaust and turbocharger system. The ship shafting system was modelled using the power balance and its efficiency. The predicted results of fuel consumption, engine delivered power and vessel speeds were tested with measured data under different engine response. The whole ship voyage model will be used to predict fuel consumption and exhaust emissions under different sailing conditions in further study.

Selection and/or peer-review under responsibility of ICAE

Marine engine; fuel consumption; engine delivered power; propeller shaft; vessel speed

1. Introduction

In order to meet the recent requirement of energy saving and CO2 emission reduction, many researches have been drawn to develop simulation model to estimate real performance of ships in the actual sea condition. The ship behavior in actual sailing condition is one of the major concerns for designers and ship owners. Ship weather-routing is defined as a procedure to determine an optimal route based on the

weather forecasts and ship hydrodynamics motion [1, 2]_{. For the propulsion power source, the propeller}

trust or engine power is set to be constant during the voyage. However, from vessel maneuvering to full cruise, the engine load changes from 10% to 80%. When the ship encounters storm or heavy sea, and the propeller works in a very hostile environment, the engine speed should be slow down to reduce non-useful output work and fuel consumption and ensuring the sailing safety. The propeller and engine compose a strongly coupled system to determine vessel speed. Therefore the engine response in waves should not be ignored when we need to evaluate fuel consumption and emissions in the actual voyage.

* Corresponding author. Tel.: (65)81098215; fax: (65)67756762.

E-mail address: [email protected].

Available online at www.sciencedirect.com

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In the present study, a marine propulsion model was built including two-stroke marine engine and fixed pitch propeller system. Coupled with vessel voyage model, a container ship could be actuated under different engine response along the desired trajectory. Then the fuel consumption during different sailing conditions could be predicted. It provides new perspective to study optimal sailing route.

1. Marine engine model

Fuel consumption is directly related to marine engine operation conditions. Normally, the larger

container ships are equipped with two-stroke marine engine with speed lower than 130rpm [3]_{as the main}

engine, delivering power to propeller. And a four-stroke marine engine is used as auxiliary engine responsible for all onboard power or off-loading equipment. In this study, the marine engine is modeled using a cycle mean value model approach in conjunction with differential equations for the fast transient power plant performance calculation of the engine crankshaft speed and delivered power. The thermodynamic and flow dynamic process in engine operation are taken into consideration. The main

components of the engine are shown in Figure 1.

Fig.1 Schematic of engine main components

For a direct injection marine diesel engine, the degree of fuel/air mixture homogeneity is very important to determine the thermal efficiency and fuel consumption. For this cycle mean value model, the

indicated thermal efficiency ηin is expressed as a function of excess air ratio based on the measured data

from MAN Diesel & Turbo Corporation [4]_{. The fuel mass flow rate is calculated by the variation of the}

mass of injected fuel per cylinder and per cycle controlled by fuel pump rack position. Thus the fuel and air mass flow rate are calculated:

mf=mfNcylne/(60revcy) (1)

ma=ηvpinlvcylNcylne(60RrevcyTinl) (2)

Where mf is the fuel mass injected into the cylinder; Ncyl is the number of cylinders; ne is the engine

rotational speed; revcy is the revolutions per cycle; pinl and Tinl are inlet pressure and temperature,

respectively; ηv is the volumetric efficiency; vcyl is the volume per cylinder, and R is the gas constant

number.

The engine output torque Qi is derived using engine indicated thermal efficiency, fuel mass flow rate

and rotational speed:

Qi=30ηiHumf/(πne) (3)

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In this study, the friction loss torque Qf due to piston reciprocating motion etc. could be expressed as a

function of friction force and engine speed. Therefore, the engine shaft rotation speed ne could be

calculated by applying the angular momentum conservation in propulsion plant system:

dne/dt=30[Qi(t-τi)-Qf-Qp]/(πIe) (4)

Where τi means the ignition delay; Qp is the propeller torque, and Ie is inertia moment of the engine.

The variance of flow mass, temperature and pressure through intake and exhaust manifold are expressed based on volume dynamic as follows:

dTout/dt=(minkTin-moutkTout-Toutdmg/dt)/mg (5)

dmg/dt=min-mout (6)

dpout/dt=kR(minTin-moutTout)/Vg (7)

Where the subscript in and out indicate the variables at the inlet and outlet of the manifold respectively. After the exhaust manifold, the exhaust gas is expanded in the turbine and then drives the compressor. Operation working map of turbocharger is necessary to get information on mass flow rate and efficiency.

2. Engine speed governor model

Incremental PID engine governor model is utilized to control the fuel injector rack position, according to the deviation of target engine speed and feedback calculated value. It highlights with little effect by faulty action. When the propeller load is changed suddenly due to the wave fluctuation or mechanical accident, the self-tuning of fuel supply could be achieved, maintaining the same engine speed in order to protect the engine integrity during fast transients.

3. Propeller model

If there is no gearbox between the two-stroke marine engine and propeller, the propeller rotation speed equals to the engine speed. When the engine delivered power and operation speed are known, the

propeller torque Qp and thrust Tp can be calculated using the dimensionless coefficients:

Qp=KQρnp2Dp5 (8)

Tp=KTρnp2Dp4 (9)

Where KQ is the non-dimensional torque coefficient; KT is the non-dimensional thrust coefficient. ρ is the

density of sea water; np is the propeller rotation speed and Dp is the diameter of the propeller.

The mathematical modeling of the ship propulsion plant was implemented in the Marine System

Simulator toolbox in Matlab/Simulink environment, as shown in Figure.2. The vessel movement is

actuated by the propeller thrust.

4. Ship hydrodynamics modelling

The accuracy of describing ship’s hydrodynamic behavior under different sailing conditions also influences the prediction of marine fuel consumption. In this study, vessel moving includes six degrees of freedom (DOF) to determine the translational and rotational movement. The first three coordinates related to position and translational motions are surge, sway and heave, corresponding with roll, pitch and yaw in

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v essel vessel data Input np Tp Qp propeller load and thrust propeller propeller data rpm ndes Tc Tc0 intercooler mc Tco Pout Tout intake system PID governor Tin min Pout Tout exhaust system Qp mf Pinl Tinl ne bsf c Eng_out Texh mexh diesel engine Ttin Ptin Tc mc Turbocharger Output To Workspace Fuel injector

Fig.2 Marine propulsion model

The vessel speed is given by the motion equation with fluid memory effects:

Mν’+CRBν+CAνr+Bνr+Gη=τ+τH (10)

Where MęR6h₆

is the sum of the system inertia matrix and the added mass matrix. CRBęR6h6 is the

Coriolis-Centripetal matrix. CAęR6h6 is the constant infinite frequency added mass matrix. νr=ν-νcęR6h6

is the relative velocity between vessel velocity ν and sea current velocity νc. BęR6h6 is the constant

infinite frequency potential damping matrix. GęR6h₆

is the restoring matrix. τęR6h₆

is the control force

vector produced by the propeller system. τHęR6h6 is a vector of time-varying hydrodynamic forces. All

the detailed definition and computation of above matrices and vectors could be found in reference [5]_.

Fig.3 The schematic diagram of 6 DOF motions for a ship

5. Results and discussion

In this study, the propulsion power plant of a typical feeder container ship S175, with a length of 175 m and a weight of 24610 ton, is simulated using the model described above. The vessel is driven by

tracking control with a type-2 fuzzy controller [6]_{, along with a desired trajectory in the presence of}

time-varying hydrodynamic disturbances. The MAN 6S60ME engine is equipped for this vessel as the main

engine [7, 8]_{. The main engine is a two-stroke marine diesel engine with one turbocharger unit. The}

maximum output power is 14280kW, considering 15% sea margin and 10% engine margin for fouling ship hull and heavy weather, in order to satisfy the maximum serving speed of approximate 20knot for

this container ship. The main engine specifications are given in Table 1. One five-blades fixed pitch

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Table 1: Specifications of the marine diesel engine

Engine 6S60ME

Bore 600 mm

Stroke 2400 mm

Number of cylinders 6

Maximum continuous rating (MCR) 14,280 kW

Engine speed (100% of MCR) 105 rpm

Specified fuel oil consumption (100% of MCR) 168 g/kWh

Turbocharger type Conventional T/C

Initially, the engine model was calibrated so that the simulation results for various response of the engine governor rack position are in good agreement with the respective ones given by the engine

manufacturer [4]_{. Comparisons of simulation and experimental results in terms of specified fuel oil}

consumption (SFOC) and engine indicated output power under different engine speed are shown in

Figure 4. The low calorific value for the test fuel is 42,700kJ/kg. The predicted fuel consumption rate and engine output power are well agreed with measured data. The accurate predictions of fuel consumption rate and engine output power under various engine loads are essential for the fuel consumption forecast during the actual ship voyage.

60 70 80 90 100 110 150 155 160 165 170 175 180 185 Experimental results Simulation results Engine speed / rpm SFOC / g/kWh 30 45 65 5% error 2% error Engine load / % 100 60 70 80 90 100 110 4.0E3 6.0E3 8.0E3 1.0E4 1.2E4 1.4E4

1.6E4 _{Experimental results} Simulation results

Engine speed / rpm

Power / kW

(a) Specified fuel oil consumption (b) Indicated engine power

Fig. 4 Comparison of simulated and measured results

0 20 40 60 80 100 0 25 50 75 100

Data from literature Simulation results of S175

20% error

Vessel speed / %

Engine load / %

Fig. 5 Relationship between engine load and vessel speed

Then the calibrated engine model in conjunction with the propeller model is used to drive the S175 container ship tracking along the desired trajectory. The calibrated vessel sailing speed under various

engine response are depicted in Figure 5, together with the vessel data related with engine loads from

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because of the inadequate prediction of wave or weather effect on resistance load, but the error is still acceptable. Another reason may due to the ignorance of other thrusters or auxiliary engines which are responsible during the maneuver process. In the future, the ship voyage model implanted with the marine propulsion model will be used to study the fuel consumption and exhaust emissions under different sailing conditions.

6. Conclusion

The mathematical model of the overall ship propulsion plant, implemented in the container ship voyage model in the MATLAB/Simulink environment, was presented. The predicted results of fuel consumption, engine delivered power and vessel speeds were validated with measured data under different engine response. The whole ship voyage model will be used to predict fuel consumption and exhaust emissions under different sailing conditions in further study.

Copyright

Authors keep full copyright over papers published in Energy Procedia

Acknowledgements

This study is supported by the research project “Analysis of Energy Consumption and Emissions by Shipping Lines” funded by Singapore Maritime Institute

References

[1] Shao W, Zhou P, Thong SK. Development of a novel forward dynamic programming method for weather routing. J Mar Sci Technol 2012;17:239-251.

[2] Lin YH, Fang MC, Yeung RW. The optimization of ship weather routing algorithm based on the composite influence of multi-dynamic elements. Applied Ocean Research 2013;43:184-194.

[3] Corbett JJ, Koehler HW. Updated emissions from ocean shipping.Journal of Geophysical Research: Atmospheres 2003;108:1-15.

[4] http://marine.man.eu/two-stroke/ceas---engine-room-dimensioning

[5] Fossen TI. Handbook of marine craft hydrodynamics and motion control. Wiley-Blackwell, United Kingdom 2011.

[6] Chen XT, Tan WW. Tracking control of surface vessels via fault-tolerant adaptive backstepping interval type-2 fuzzy control. Ocean Engineering 2013;70:97-109.

[7] Basic Principles of Ship Propulsion, MAN Diesel & Turbo publication. [8] Propulsion Trends in Container Vessels,MAN Diesel & Turbo publication [9] Propulsion of 2,200-2,800 teu container vessels, MAN Diesel & Turbo publication [10] Turbocharging - Status & Developments, ABB company

Biography

Feiyang Zhao obtained Ph.D. degree in 2013 from State Key Lab of Engine of Tianjin University in China, majored in diesel engine combustion simulation. Now she is a research fellow working on optimizing the operation and fuel management for vessel propulsion system in NUS.